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Why You Should Consider NoSQL for Your Application

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The world today is increasingly moving towards big data. Such data helps create experiences that are geared towards the user, but it is not easy to handle. One of the technologies that have come to help meet the dynamic and versatile nature of today’s data needs is NoSQL. This type of database is different in that it doesn’t rely on tables or use SQL as its primary query language.

So, what advantages does it bring over the traditional databases we are used to? Here are some reasons why you might want to consider NoSQL for your application.

Scalability & Flexibility

NoSQL databases are known for offering great flexibility and scalability. This is because the schema of these databases is not based on a rigid structure. It can be changed as needed, which allows developers to adapt to new data needs. This makes NoSQL a great option if you are working on an application that deals with unstructured or semi-structured data.

Besides the flexibility, NoSQL databases are famous for their ability to scale horizontally. In vertical scaling, you would need to upgrade things such as the CPU, memory, and storage of your server. Horizontal scaling simplifies things by allowing you to simply add another server to the network. It’s therefore a superb choice if you anticipate that your application will greatly increase in usage.

Handling Diverse Data Types

Relation databases are based on a predefined schema. The data has to be loaded into the database and then retrieved using SQL. The fact that NoSQL uses a flexible schema means that you can use it to operate with a wide array of data types. This is quite useful as today’s data needs are quite varied. You may need to deal with documents, social media content, multi-media files, etc. NoSQL can support all this, whether structured or unstructured, with ease.

This ability to handle varied data types means that you won’t have to limit your application. You can incorporate any data sources you’d like, including IOT devices. 

High Performance and Speed

Relational databases use multiple table joins, something that often makes them slow. Non-relational ones have a much better approach to the retrieval process. They are based on denormalized data models, which means that there’s no need for complexity, and access to data is streamlined. This usually results in faster read operations.

Besides this, the horizontal scalability of non-relational databases greatly helps to ensure speed. You won’t need to shift to larger computers, which may not be easy or easily affordable. Adding more nodes or servers is enough on NoSQL as the database can distribute its operations. All user requests will be processed swiftly, and you can easily adapt to increased traffic.

Enhanced Availability and Fault Tolerance

SQL databases are based on a specific server. This means that if the server fails, the application fails (single point of failure). NoSQL helps overcome this challenge as it operates on a distributed architecture. Operations of the database are carried out across multiple nodes or data centers. When one fails, the others still continue to operate, meaning that you have resilience against hardware failures.

To make this possible, NoSQL has mechanisms that replicate the data over the different nodes. This is also combined with various consistency models, and the developer can choose the amount of consistency they want. 

Cost-Efficiency

When you want to increase the resources in relational databases, you have to purchase high-end hardware, which is costly. This is not the case for NoSQL, as you only need to add an extra server. You can therefore scale up or down and keep the costs of hardware and operations low. 

But even besides scaling, you can also opt for cloud-managed services, which means that you avoid the initial costs. NoSQL databases also don’t require much maintenance as they are dynamic and have automated sharding. This makes such databases appealing if you want to optimize costs and benefit from the scalability and dynamic way of handling data.

 

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